Artificial Intelligence Based Fractional Order PID Control Strategy for Active Magnetic Bearing

Conventional PID controllers are commonly used in active magnetic bearing systems and encounter some stability problems during extremely dynamic operation. This paper proposed a fractional order proportional-integral-derivative (FO-PID) controller to improve the stability and performance of the active magnetic bearing (AMB) system. In comparison to traditional PID controller, FOPID controllers have five control variables- proportional, integral, integral order, derivative, and derivative order. In this research work, Single coil A-AMB designed in a laboratory has been controlled utilizing the FOPID controller. Using artificial intelligence methods, such as particle swarm optimization the five FO-PID variables and three PID control variables are calibrated and the controllers evaluated. The process overshoot condition and the time specification constraints are considered in the optimization technique. For validating the simulation results hardware prototype is fabricated.